Triple
T6746140
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arlon |
E154217
|
entity |
| Predicate | hasTwinTown |
P919
|
FINISHED |
| Object | Lippstadt |
E567830
|
NE FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Lippstadt | Statement: [Arlon, hasTwinTown, Lippstadt]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lippstadt Context triple: [Arlon, hasTwinTown, Lippstadt]
-
A.
Lippstadt
chosen
Lippstadt is a historic town in North Rhine-Westphalia, Germany, known for its medieval architecture and role in regional conflicts.
-
B.
Remscheid
Remscheid is a city in North Rhine-Westphalia, Germany, known historically for its metalworking industry and as the birthplace of physicist Wilhelm Röntgen.
-
C.
Jülich
Jülich is a historic town in western Germany, known for its former status as a ducal residence and its significant Renaissance-era fortifications.
-
D.
Gardelegen
Gardelegen is a historic town in the German state of Saxony-Anhalt, known for its medieval architecture and its location in the Altmark region.
-
E.
Detmold
Detmold is a historic town in northwestern Germany that served as the capital and residence city of the former Principality of Lippe.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69c6880ef37881909268a5a7299b9293 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d1b8a0f0819086b802983e8ffcb6 |
completed | March 27, 2026, 6:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c9c89d62c08190b575d7e1058afbeb |
completed | March 30, 2026, 12:49 a.m. |
Created at: March 27, 2026, 2:10 p.m.